The present invention is in the technical field of measurement of electric parameters.
More particularly, the present invention is in the technical field of stability measurements of an alternating current (a.c.) power grid.
Every a.c. power grid has a nominal fundamental frequency, such as 50 Hertz or 60 Hertz. Every a.c. power grid has a nominal fundamental period, which is a time that is the inverse of the frequency: 20 milliseconds fundamental period for 50 Hertz, 16.667 milliseconds for 60 Hertz.
Every section of an a.c. power grid has a nominal voltage, which is the ‘name’ or approximate expected voltage, such as 120 volts, or 230 volts, or 24 kilovolts. Each physical location on an a.c. power grid also has an actual voltage, which is the voltage that is present at that location at a particular instant in time, for example 129.374 volts or 23.878 kilovolts. Due to changes in load, changes in grid impedance, and changes in generation, the actual voltage at any location is not constant. In almost any practical grid, in the actual voltage at any location we find a phenomena we will call a ‘background voltage variation’ that, over a period of a few seconds, will cause the actual voltage to change. Such changes can be 500 parts per million (500 PPM, or 0.05%) or more.
Traditionally, a.c. power grids move a.c. energy from a spinning electro-mechanical generator to a large collection of geographically dispersed end-use loads. A typical generator converts a supply of thermal or hydro-electric energy into a.c. energy.
In traditional a.c. power grids, energy flows through the a.c. power grid in one direction: from the generator to the end-use loads.
Traditional end-use loads were both linear and straightforward, such as motors, lights, and heaters.
The current drawn by the loads causes the actual voltages at all locations on an a.c. grid to change. For example, if the current in a house abruptly increases because a refrigerator compressor motor turns on, the voltage in the house will abruptly decrease, sometimes causing lights to dim slightly. The magnitude of the change in voltage is determined by the magnitude of the change in current and the source impedance of the a.c. grid at that location.
In modern a.c. power grids, inverters are also used to generate a.c. electric power. When attached to an a.c. grid, an inverter is effectively a generator. ‘Inverters’ are electronic devices that convert direct current (d.c.) power into a.c. power. In a modern a.c. grid, generators such as fuel cell inverters, battery inverters, and photovoltaic solar inverters, can be found attached directly to the grid, which can cause energy to flow in unexpected directions on these portions of the grid.
Further, the inverters contain electronic or software control loops that help them track and match the frequency and voltage of the a.c. grid to which they are attached. Different inverters can have different time constants built into their control loops, and when two or more such inverters are connected to the same grid, the control loops in the inverters can oscillate against each other, oscillate in unison, or become otherwise unstable. This effect is particularly pronounced during transitory step changes in voltage or frequency on the a.c. power grid to which they are attached.
Further, unlike traditional spinning electro-mechanical generators, inverters have no rotational inertia, and thus are inherently less stable.
In modern grids, an increasing proportion of loads, such as variable frequency drives and electric vehicle chargers, have intentional or unintentional feedback loops that adjust their current consumption from the grid based on voltage changes on the grid.
Modern grids can possibly become unstable, in some cases because of interactions between control loops in inverters and control loops in modern loads. To avoid these instabilities, on many a.c. power grids, limits have been placed on the amount of inverter-supplied power. These limits can restrict the deployment of useful technologies, including solar power and wind power. These limits are based on simulations and rules of thumb, not real world real-time measurements, in part because it is difficult to directly measure the stability of a power grid. These simulations and rules of thumb can be less than accurate because the stability characteristics of a grid often change rapidly, when, for example, the sun comes out from behind a cloud, or a collection of electric vehicle chargers activate. In addition, stability of modern electric a.c. power grids and connected devices are difficult to characterize during steady-state conditions.
For these reasons, among others, it would be useful to have tools to actively and precisely perturb a.c. power grids and then measure and characterize the stability of an a.c. power grid, while it is operating in real time.
Many of the economically valuable loads that are supplied by an alternating current power grid, including bank computers, automated teller machines, cash registers, telecommunication switches, and the like, are, from an power grid perspective, sensitive loads: they can be disrupted by abrupt changes in actual grid voltage, waveform, or the like. For example, international Standards such as IEC 61000-4-30, published by the International Electrotechnical Commission, and IEEE 519, published by the International Electrical and Electronic Engineers, and SEMI F47, published by the Semiconductor Equipment Manufacturers Institute, all suggest that sensitive equipment can tolerate a brief 10% reduction in actual voltage, but no more. (The first named inventor on the present application has served as the Chair of all three of these Standards.)
It would be useful to measure the stability of an a.c. power distribution grid without disrupting these sensitive loads.
It is well known in the prior art that one can measure the stability of any system that contains one or more control feedback loops by stimulating the system with an impulse, while observing the system output before, during, and after the impulse stimulation. Often, one or more damped oscillations can be observed in the system output. The frequency or frequencies of those oscillations can provide useful information about stability risks in the system, and the damping can be a useful measure of the system stability. Damping is the length of time, or number of oscillations, it takes for the system to return to a steady state output, if it ever does. For example, a child sitting on a swing has a feedback loop. The further the child is moved away from the centered, stable, hanging position, the more force is available to move the child back to the center position. The feedback loop has damping, primarily in the mechanical friction of the swing's bearings. The child's swing system has a resonant frequency, too. The resonant frequency and the damping can be observed and measured simply by applying an impulse to the system, i.e. pushing the child once. The resonant frequency of the system can be observed by timing the swing's subsequent oscillations. The damping of the system can be observed by measuring the time that elapses before the swing returns to its steady-state position, hanging straight down (and the child, finding the steady state somewhat boring, asks to be pushed again).